What is included with this book?
Preface | |
Statistical packages | |
Data Types | |
Data types | |
Does it really matter? | |
Interval scale data | |
Ordinal scale data | |
Nominal scale data | |
Structure of this book | |
Chapter summary | |
Interval-Scale Data | |
Descriptive statistics | |
Summarizing data sets | |
Indicators of central tendency. mean, median and mode | |
Describing variability. standard deviation and coefficient of variation | |
Quartiles. another way to describe data | |
Using computer packages to generate descriptive statistics | |
Chapter summary | |
The normal distribution | |
What is a normal distribution? | |
Identifying data that are not normally distributed | |
Proportions of individuals within one or two standard deviations of the mean | |
Chapter summary | |
Sampling from populations. the SEM | |
Samples and populations | |
From sample to population | |
Types of sampling error | |
What factors control the extent of random sampling error? | |
Estimating likely sampling error. The SEM | |
Offsetting sample size against standard deviation | |
Chapter summary | |
Ninety-five per cent confidence interval for the mean | |
What is a confidence interval? | |
How wide should the interval be? | |
What do we mean by '95 per cent' confidence? | |
Calculating the interval width | |
A long series of samples and 95 per cent confidence intervals | |
How sensitive is the width of the confidence interval to changes in the SD, the sample size or the required level of confidence? | |
Two statements | |
One-sided 95 per cent confidence intervals | |
The 95 per cent confidence interval for the difference between two treatments | |
The need for data to follow a normal distribution and data transformation | |
Chapter summary | |
The two-sample t-test(1).Introducing hypothesis tests | |
The two-sample t-test. an example of a hypothesis test | |
'Significance' | |
The risk of a false positive finding | |
What factors will influence whether or not we obtain a significant outcome? | |
Requirements for applying a two-sample t-test | |
Chapter summary | |
The two-sample t-test(2).The dreaded P value | |
Measuring how significant a result is | |
P values | |
Two ways to define significance? | |
Obtaining the P value | |
P values or 95 per cent confidence intervals? | |
Chapter summary | |
The two-sample t-test(3).False negatives, power and necessary sample sizes | |
What else could possibly go wrong? | |
Power | |
Calculating necessary sample size | |
Chapter summary | |
The two-sample t-test(4).Statistical significance, practical significance and equivalence | |
Practical significance. is the difference big enough to matter? | |
Equivalence testing | |
Non-inferiority testing | |
P values are less informative and can be positively misleading | |
Setting equivalence limits prior to experimentation | |
Chapter summary | |
The two-sample t-test(5).One-sided testing | |
Looking for a change in a specified direction | |
Protection against false positives | |
Temptation! | |
Using a computer package to carry out a one-sided test | |
Should one-sided tests be used more commonly? | |
Chapter summary | |
What does a statistically significant result really tell us? | |
Interpreting statistical significance | |
Starting from extreme scepticism | |
Chapter summary | |
The paired t-test. comparing two related s | |
Table of Contents provided by Publisher. All Rights Reserved. |
The New copy of this book will include any supplemental materials advertised. Please check the title of the book to determine if it should include any access cards, study guides, lab manuals, CDs, etc.
The Used, Rental and eBook copies of this book are not guaranteed to include any supplemental materials. Typically, only the book itself is included. This is true even if the title states it includes any access cards, study guides, lab manuals, CDs, etc.